Director of AI Engineering (Transformation Team)

Mastercard; New York (NY); On-site; USD 210,000 - 260,000; Full time

Job summary

Mastercard is seeking a senior AI/ML leader to develop and execute short- and mid-term AI Engineering plans that align with organizational objectives. You will translate business needs into scalable AI solutions, partnering with product, data science, and operations to drive impact and governance across projects.

You will oversee the ML lifecycle from architecture to deployment, ensure robust monitoring, and mentor senior technical leads in a fast-paced environment.

Qualifications

• Experience bridging model development and real-world application.
• Hands-on understanding of transformer architectures and generative AI.
• Proficiency in Python and ML frameworks (PyTorch/TensorFlow).
• Experience with data engineering and MLOps to support training, evaluation, and inference at scale.

Responsibilities

• Develop and execute AI/ML strategy and plans.
• Translate organizational priorities into scalable AI solutions and operational strategies.
• Oversee ML engineering lifecycle from architecture to deployment and monitoring.
• Ensure model governance, ethics, and risk management across AI/ML systems.
• Provide technical guidance and mentorship to senior leads.

Skills

Transformer architectures

Generative AI

Python

ML frameworks

Production deployment

MLOps

Effective communication

Stakeholder management

Tools

PyTorch

TensorFlow

Job description

• The Transformation Team leads strategic change initiatives to reimagine how Mastercard works and scales, simplifies, and accelerates business outcomes
• The team partners across leadership, product, technology, and operations to design and implement new organizational models, embed AI across key workflows, drive enterprise-wide transformation programs, improve operating effectiveness, and ensure successful adoption of change
• By combining strategy, AI engineering, organizational design, change management, and program execution, the team helps align people, processes, and priorities to support long-term growth and business performance
• This job develops and executes short-term and medium-term strategic plans for AI Engineering across Mastercard, aligning functional initiatives with organizational objectives by modifying existing methods to make significant improvements to existing processes, programs, and/or policies
• Drives the development and execution of short-term functional strategies for AI/ML teams, translating organizational priorities into actionable plans and deliverables
• Collaborates with product and business leaders to translate organizational needs into scalable AI solutions and operational strategies
• Oversees the ML engineering lifecycle of AI/ML projects, from architecture, design to deployment and monitoring, ensuring timely delivery within scope and budget
• Leads cross-functional teams in optimizing, fine-tuning, and deploying models that meet performance, robustness, and ethical standards, ensuring operational stability, scalability, and compliance of AI/ML systems, including model governance, ethical standards, and risk management
• Provides technical guidance and mentorship to senior technical leads, supporting their professional growth and ensuring technical excellence
• Serves as a key stakeholder and influencer in cross-functional initiatives, working closely with product managers, data scientists, and business units to align AI/ML solutions with strategic objectives
• Defines and refines best practices, standards, and methodologies for AI/ML optimization, deployment, and maintenance, ensuring consistency and high-quality outputs
• Contributes to organizational strategy by identifying emerging trends, evaluating new technologies, and recommending investments in AI/ML capabilities
• Abide by Mastercard’s security policies and practices
• Ensure the confidentiality and integrity of the information being accessed
• Report any suspected information security violation or breach
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines

Experience bridging model development and real-world application, translating AI capabilities into business impactStrong hands-on understanding of transformer architectures and generative AI, including fine-tuning, prompting, embeddings, and evaluationComfortable operating in a fast-moving, evolving AI landscape with ambiguity and shifting prioritiesSolid engineering background, with familiarity in Python, ML frameworks (e.g. PyTorch/TensorFlow), and production deployment patternsExperience working with data engineering and MLOps practices to support training, evaluation, and inference at scaleExcellent communication skills, able to articulate complex AI concepts to both technical and non-technical audiencesStrong stakeholder management skills, with the ability to align technical delivery to business priorities and measurable outcomes